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      A Systematic Review and Integrated Bioinformatic Analysis of Candidate Genes and Pathways in the Endometrium of Patients With Polycystic Ovary Syndrome During the Implantation Window


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          Polycystic ovary syndrome (PCOS) is a common disorder with wide-ranging clinical heterogeneity that causes infertility. However, the comprehensive molecular mechanisms of PCOS in causing infertility is remaining unclear. Hence, a comprehensive literature search was conducted using PubMed, Scopus, EBSCOhost, and Science Direct. Medical Subject Heading (MeSH) terms like PCOS, gene expression, implantation window and endometrium were used as the keywords. From 138 studies retrieved, original articles with RNA profiling on human endometrial tissues in PCOS women during the implantation window were included. Study design, sample size, sample type, method, and differentially expressed genes (DEGs) were identified from all publications. The DEGs were analyzed using the software packages DAVID, STRING, and Cytoscape. Three studies that met inclusion criteria were included, and 368 DEGs were identified. Twelve significant clusters from the protein-protein interaction network (PPI) complex were found, and cluster 1 showed very high intermolecular interactions. Five candidate genes (AURKA, CDC25C, KIF23, KIF2C, and NDC80) were identified from the systematic review and integrated bioinformatics analysis. It is concluded that cell cycle is the fundamental biological processes that were dysregulated in the endometrium of PCOS women, affecting decidualization progression in the endometrium during the implantation window.

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          Most cited references33

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

            DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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              Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

              Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.

                Author and article information

                URI : https://loop.frontiersin.org/people/1614519
                URI : https://loop.frontiersin.org/people/1136563
                URI : https://loop.frontiersin.org/people/1079683
                Front Endocrinol (Lausanne)
                Front Endocrinol (Lausanne)
                Front. Endocrinol.
                Frontiers in Endocrinology
                Frontiers Media S.A.
                01 July 2022
                : 13
                : 900767
                [1] 1 Department of Obstetrics & Gynecology, Faculty of Medicine, Universiti Kebangsaan Malaysia , Kuala Lumpur, Malaysia
                [2] 2 Faculty of Medicine & Health Sciences, Universiti Sains Islam Malaysia , Bandar Baru Nilai, Malaysia
                Author notes

                Edited by: Maryam Shabani Nashtaei, Tehran University of Medical Sciences, Tehran, Iran

                Reviewed by: Edmund Baracat, University of São Paulo, Brazil; Fang Wang, Lanzhou University Second Hospital, China

                *Correspondence: Muhammad Azrai Abu, azraiabu1983@ 123456gmail.com

                This article was submitted to Reproduction, a section of the journal Frontiers in Endocrinology

                Copyright © 2022 Sutaji, Elias, Ahmad, Karim and Abu

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                : 21 March 2022
                : 01 June 2022
                Page count
                Figures: 3, Tables: 3, Equations: 0, References: 34, Pages: 10, Words: 5133
                Funded by: Ministry of Higher Education, Malaysia , doi 10.13039/501100003093;
                Systematic Review

                Endocrinology & Diabetes
                polycystic ovary syndrome,implantation window,endometrium,differentially expressed genes,systematic review


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